기계 번역으로 제공되는 번역입니다. 제공된 번역과 원본 영어의 내용이 상충하는 경우에는 영어 버전이 우선합니다.
# 이미지에서 개인 보호 장비 감지
이미지에서 사람이 착용하고 있는 PPE(개인 보호 장비)를 감지하려면 [DetectProtectiveEquipment](https://docs.aws.amazon.com/rekognition/latest/APIReference/API_DetectProtectiveEquipment.html) 비스토리지 API 작업을 사용하세요.
입력 이미지는 AWS SDK나 AWS Command Line Interface (AWS CLI)를 사용하여 이미지 바이트 배열(base64 인코딩된 이미지 바이트) 또는 Amazon S3 객체로 넣을 수 있습니다. 다음 예제에서는 Amazon S3 버킷에 저장된 이미지를 사용합니다. 자세한 내용은 [이미지 작업](images.md) 단원을 참조하십시오.
**이미지 내 사람의 PPE를 감지하려면**
1. 아직 설정하지 않았다면 다음과 같이 하세요.
1. `AmazonRekognitionFullAccess` 권한과 `AmazonS3ReadOnlyAccess` 권한을 가진 사용자를 생성하거나 업데이트합니다. 자세한 내용은 [1단계: AWS 계정 설정 및 사용자 생성](setting-up.md#setting-up-iam) 단원을 참조하십시오.
1. AWS CLI 및 AWS SDKs를 설치하고 구성합니다. 자세한 내용은 [2단계: AWS CLI 및 AWS SDKs 설정](setup-awscli-sdk.md) 단원을 참조하십시오.
1. (PPE를 착용하고 있는 한 명 이상의 사람이 포함된) 이미지를 S3 버킷에 업로드합니다.
이에 관한 지침은 *Amazon Simple Storage Service 사용 설명서*에서 [Amazon S3에 객체 업로드](https://docs.aws.amazon.com/AmazonS3/latest/userguide/UploadingObjectsintoAmazonS3.html)를 참조하세요.
1. 다음 예제를 사용하여 `DetectProtectiveEquipment` 작업을 호출합니다. 이미지에 경계 상자를 표시하는 방법에 대한 자세한 내용은 [경계 상자 표시](images-displaying-bounding-boxes.md) 섹션을 참조하세요.
------
#### [ Java ]
이 예제에서는 이미지 내 감지된 사람에게서 감지된 PPE 항목에 대한 정보를 표시합니다.
`amzn-s3-demo-bucket`의 값을 이미지 파일이 저장된 Amazon S3 버킷의 이름으로 바꿉니다. `photo`의 값을 이미지 파일 이름으로 변경합니다.
```
//Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
//PDX-License-Identifier: MIT-0 (For details, see https://github.com/awsdocs/amazon-rekognition-developer-guide/blob/master/LICENSE-SAMPLECODE.)
package com.amazonaws.samples;
import com.amazonaws.client.builder.AwsClientBuilder;
import com.amazonaws.services.rekognition.AmazonRekognition;
import com.amazonaws.services.rekognition.AmazonRekognitionClientBuilder;
import com.amazonaws.services.rekognition.model.AmazonRekognitionException;
import com.amazonaws.services.rekognition.model.Image;
import com.amazonaws.services.rekognition.model.ProtectiveEquipmentBodyPart;
import com.amazonaws.services.rekognition.model.S3Object;
import com.amazonaws.services.rekognition.model.ProtectiveEquipmentPerson;
import com.amazonaws.services.rekognition.model.ProtectiveEquipmentSummarizationAttributes;
import java.util.List;
import com.amazonaws.services.rekognition.model.BoundingBox;
import com.amazonaws.services.rekognition.model.DetectProtectiveEquipmentRequest;
import com.amazonaws.services.rekognition.model.DetectProtectiveEquipmentResult;
import com.amazonaws.services.rekognition.model.EquipmentDetection;
public class DetectPPE {
public static void main(String[] args) throws Exception {
String photo = "photo";
String bucket = "bucket";
AmazonRekognition rekognitionClient = AmazonRekognitionClientBuilder.defaultClient();
ProtectiveEquipmentSummarizationAttributes summaryAttributes = new ProtectiveEquipmentSummarizationAttributes()
.withMinConfidence(80F)
.withRequiredEquipmentTypes("FACE_COVER", "HAND_COVER", "HEAD_COVER");
DetectProtectiveEquipmentRequest request = new DetectProtectiveEquipmentRequest()
.withImage(new Image()
.withS3Object(new S3Object()
.withName(photo).withBucket(bucket)))
.withSummarizationAttributes(summaryAttributes);
try {
System.out.println("Detected PPE for people in image " + photo);
System.out.println("Detected people\n---------------");
DetectProtectiveEquipmentResult result = rekognitionClient.detectProtectiveEquipment(request);
List persons = result.getPersons();
for (ProtectiveEquipmentPerson person: persons) {
System.out.println("ID: " + person.getId());
List bodyParts=person.getBodyParts();
if (bodyParts.isEmpty()){
System.out.println("\tNo body parts detected");
} else
for (ProtectiveEquipmentBodyPart bodyPart: bodyParts) {
System.out.println("\t" + bodyPart.getName() + ". Confidence: " + bodyPart.getConfidence().toString());
List equipmentDetections=bodyPart.getEquipmentDetections();
if (equipmentDetections.isEmpty()){
System.out.println("\t\tNo PPE Detected on " + bodyPart.getName());
}
else {
for (EquipmentDetection item: equipmentDetections) {
System.out.println("\t\tItem: " + item.getType() + ". Confidence: " + item.getConfidence().toString());
System.out.println("\t\tCovers body part: "
+ item.getCoversBodyPart().getValue().toString() + ". Confidence: " + item.getCoversBodyPart().getConfidence().toString());
System.out.println("\t\tBounding Box");
BoundingBox box =item.getBoundingBox();
System.out.println("\t\tLeft: " +box.getLeft().toString());
System.out.println("\t\tTop: " + box.getTop().toString());
System.out.println("\t\tWidth: " + box.getWidth().toString());
System.out.println("\t\tHeight: " + box.getHeight().toString());
System.out.println("\t\tConfidence: " + item.getConfidence().toString());
System.out.println();
}
}
}
}
System.out.println("Person ID Summary\n-----------------");
//List list=;
DisplaySummary("With required equipment", result.getSummary().getPersonsWithRequiredEquipment());
DisplaySummary("Without required equipment", result.getSummary().getPersonsWithoutRequiredEquipment());
DisplaySummary("Indeterminate", result.getSummary().getPersonsIndeterminate());
} catch(AmazonRekognitionException e) {
e.printStackTrace();
}
}
static void DisplaySummary(String summaryType,List idList)
{
System.out.print(summaryType + "\n\tIDs ");
if (idList.size()==0) {
System.out.println("None");
}
else {
int count=0;
for (Integer id: idList ) {
if (count++ == idList.size()-1) {
System.out.println(id.toString());
}
else {
System.out.print(id.toString() + ", ");
}
}
}
System.out.println();
}
}
```
------
#### [ Java V2 ]
이 코드는 AWS 설명서 SDK 예제 GitHub 리포지토리에서 가져온 것입니다. 전체 예제는 [여기](https://github.com/awsdocs/aws-doc-sdk-examples/blob/master/javav2/example_code/rekognition/src/main/java/com/example/rekognition/DetectPPE.java)에서 확인하세요.
```
//snippet-start:[rekognition.java2.detect_ppe.import]
import software.amazon.awssdk.auth.credentials.ProfileCredentialsProvider;
import software.amazon.awssdk.core.ResponseBytes;
import software.amazon.awssdk.core.SdkBytes;
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.rekognition.RekognitionClient;
import software.amazon.awssdk.services.rekognition.model.BoundingBox;
import software.amazon.awssdk.services.rekognition.model.DetectProtectiveEquipmentRequest;
import software.amazon.awssdk.services.rekognition.model.DetectProtectiveEquipmentResponse;
import software.amazon.awssdk.services.rekognition.model.EquipmentDetection;
import software.amazon.awssdk.services.rekognition.model.ProtectiveEquipmentBodyPart;
import software.amazon.awssdk.services.rekognition.model.ProtectiveEquipmentSummarizationAttributes;
import software.amazon.awssdk.services.rekognition.model.Image;
import software.amazon.awssdk.services.rekognition.model.RekognitionException;
import software.amazon.awssdk.services.s3.S3Client;
import software.amazon.awssdk.services.s3.model.GetObjectRequest;
import software.amazon.awssdk.services.s3.model.GetObjectResponse;
import software.amazon.awssdk.services.s3.model.S3Exception;
import software.amazon.awssdk.services.rekognition.model.ProtectiveEquipmentPerson;
import java.io.ByteArrayInputStream;
import java.io.InputStream;
import java.util.List;
//snippet-end:[rekognition.java2.detect_ppe.import]
/**
* Before running this Java V2 code example, set up your development environment, including your credentials.
*
* For more information, see the following documentation topic:
*
* https://docs.aws.amazon.com/sdk-for-java/latest/developer-guide/get-started.html
*/
public class DetectPPE {
public static void main(String[] args) {
final String usage = "\n" +
"Usage: " +
" \n\n" +
"Where:\n" +
" sourceImage - The name of the image in an Amazon S3 bucket (for example, people.png). \n\n" +
" bucketName - The name of the Amazon S3 bucket (for example, amzn-s3-demo-bucket). \n\n";
if (args.length != 2) {
System.out.println(usage);
System.exit(1);
}
String sourceImage = args[0];
String bucketName = args[1];
Region region = Region.US_WEST_2;
S3Client s3 = S3Client.builder()
.region(region)
.credentialsProvider(ProfileCredentialsProvider.create("profile-name"))
.build();
RekognitionClient rekClient = RekognitionClient.builder()
.region(region)
.credentialsProvider(ProfileCredentialsProvider.create("profile-name"))
.build();
displayGear(s3, rekClient, sourceImage, bucketName) ;
s3.close();
rekClient.close();
System.out.println("This example is done!");
}
// snippet-start:[rekognition.java2.detect_ppe.main]
public static void displayGear(S3Client s3,
RekognitionClient rekClient,
String sourceImage,
String bucketName) {
byte[] data = getObjectBytes (s3, bucketName, sourceImage);
InputStream is = new ByteArrayInputStream(data);
try {
ProtectiveEquipmentSummarizationAttributes summarizationAttributes = ProtectiveEquipmentSummarizationAttributes.builder()
.minConfidence(80F)
.requiredEquipmentTypesWithStrings("FACE_COVER", "HAND_COVER", "HEAD_COVER")
.build();
SdkBytes sourceBytes = SdkBytes.fromInputStream(is);
software.amazon.awssdk.services.rekognition.model.Image souImage = Image.builder()
.bytes(sourceBytes)
.build();
DetectProtectiveEquipmentRequest request = DetectProtectiveEquipmentRequest.builder()
.image(souImage)
.summarizationAttributes(summarizationAttributes)
.build();
DetectProtectiveEquipmentResponse result = rekClient.detectProtectiveEquipment(request);
List persons = result.persons();
for (ProtectiveEquipmentPerson person: persons) {
System.out.println("ID: " + person.id());
List bodyParts=person.bodyParts();
if (bodyParts.isEmpty()){
System.out.println("\tNo body parts detected");
} else
for (ProtectiveEquipmentBodyPart bodyPart: bodyParts) {
System.out.println("\t" + bodyPart.name() + ". Confidence: " + bodyPart.confidence().toString());
List equipmentDetections=bodyPart.equipmentDetections();
if (equipmentDetections.isEmpty()){
System.out.println("\t\tNo PPE Detected on " + bodyPart.name());
} else {
for (EquipmentDetection item: equipmentDetections) {
System.out.println("\t\tItem: " + item.type() + ". Confidence: " + item.confidence().toString());
System.out.println("\t\tCovers body part: "
+ item.coversBodyPart().value().toString() + ". Confidence: " + item.coversBodyPart().confidence().toString());
System.out.println("\t\tBounding Box");
BoundingBox box =item.boundingBox();
System.out.println("\t\tLeft: " +box.left().toString());
System.out.println("\t\tTop: " + box.top().toString());
System.out.println("\t\tWidth: " + box.width().toString());
System.out.println("\t\tHeight: " + box.height().toString());
System.out.println("\t\tConfidence: " + item.confidence().toString());
System.out.println();
}
}
}
}
System.out.println("Person ID Summary\n-----------------");
displaySummary("With required equipment", result.summary().personsWithRequiredEquipment());
displaySummary("Without required equipment", result.summary().personsWithoutRequiredEquipment());
displaySummary("Indeterminate", result.summary().personsIndeterminate());
} catch (RekognitionException e) {
e.printStackTrace();
System.exit(1);
}
}
public static byte[] getObjectBytes (S3Client s3, String bucketName, String keyName) {
try {
GetObjectRequest objectRequest = GetObjectRequest
.builder()
.key(keyName)
.bucket(bucketName)
.build();
ResponseBytes objectBytes = s3.getObjectAsBytes(objectRequest);
return objectBytes.asByteArray();
} catch (S3Exception e) {
System.err.println(e.awsErrorDetails().errorMessage());
System.exit(1);
}
return null;
}
static void displaySummary(String summaryType,List idList) {
System.out.print(summaryType + "\n\tIDs ");
if (idList.size()==0) {
System.out.println("None");
} else {
int count=0;
for (Integer id: idList ) {
if (count++ == idList.size()-1) {
System.out.println(id.toString());
} else {
System.out.print(id.toString() + ", ");
}
}
}
System.out.println();
}
// snippet-end:[rekognition.java2.detect_ppe.main]
}
```
------
#### [ AWS CLI ]
이 AWS CLI 명령은 PPE 요약을 요청하고 `detect-protective-equipment` CLI 작업에 대한 JSON 출력을 표시합니다.
`amzn-s3-demo-bucket`을 이미지가 저장된 Amazon S3 버킷의 이름으로 변경합니다. `input.jpg`를 사용하고자 하는 이미지의 이름으로 변경합니다.
```
aws rekognition detect-protective-equipment \
--image "S3Object={Bucket=amzn-s3-demo-bucket,Name=input.jpg}" \
--summarization-attributes "MinConfidence=80,RequiredEquipmentTypes=['FACE_COVER','HAND_COVER','HEAD_COVER']"
```
이 AWS CLI 명령은 `detect-protective-equipment` CLI 작업에 대한 JSON 출력을 표시합니다.
`amzn-s3-demo-bucket`을 이미지가 저장된 Amazon S3 버킷의 이름으로 변경합니다. `input.jpg`를 사용하고자 하는 이미지의 이름으로 변경합니다.
```
aws rekognition detect-protective-equipment \
--image "S3Object={Bucket=amzn-s3-demo-bucket,Name=input.jpg}"
```
------
#### [ Python ]
이 예제에서는 이미지 내 감지된 사람에게서 감지된 PPE 항목에 대한 정보를 표시합니다.
`amzn-s3-demo-bucket`의 값을 이미지 파일이 저장된 Amazon S3 버킷의 이름으로 바꿉니다. `photo`의 값을 이미지 파일 이름으로 변경합니다. Rekognition 세션을 생성하는 라인에서 `profile_name`의 값을 개발자 프로필의 이름으로 대체합니다.
```
# Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# PDX-License-Identifier: MIT-0 (For details, see https://github.com/awsdocs/amazon-rekognition-developer-guide/blob/master/LICENSE-SAMPLECODE.)
import boto3
def detect_ppe(photo, bucket):
session = boto3.Session(profile_name='profile-name')
client = session.client('rekognition')
response = client.detect_protective_equipment(Image={'S3Object': {'Bucket': bucket, 'Name': photo}},
SummarizationAttributes={'MinConfidence': 80,
'RequiredEquipmentTypes': ['FACE_COVER',
'HAND_COVER',
'HEAD_COVER']})
print('Detected PPE for people in image ' + photo)
print('\nDetected people\n---------------')
for person in response['Persons']:
print('Person ID: ' + str(person['Id']))
print('Body Parts\n----------')
body_parts = person['BodyParts']
if len(body_parts) == 0:
print('No body parts found')
else:
for body_part in body_parts:
print('\t' + body_part['Name'] + '\n\t\tConfidence: ' + str(body_part['Confidence']))
print('\n\t\tDetected PPE\n\t\t------------')
ppe_items = body_part['EquipmentDetections']
if len(ppe_items) == 0:
print('\t\tNo PPE detected on ' + body_part['Name'])
else:
for ppe_item in ppe_items:
print('\t\t' + ppe_item['Type'] + '\n\t\t\tConfidence: ' + str(ppe_item['Confidence']))
print('\t\tCovers body part: ' + str(
ppe_item['CoversBodyPart']['Value']) + '\n\t\t\tConfidence: ' + str(
ppe_item['CoversBodyPart']['Confidence']))
print('\t\tBounding Box:')
print('\t\t\tTop: ' + str(ppe_item['BoundingBox']['Top']))
print('\t\t\tLeft: ' + str(ppe_item['BoundingBox']['Left']))
print('\t\t\tWidth: ' + str(ppe_item['BoundingBox']['Width']))
print('\t\t\tHeight: ' + str(ppe_item['BoundingBox']['Height']))
print('\t\t\tConfidence: ' + str(ppe_item['Confidence']))
print()
print()
print('Person ID Summary\n----------------')
display_summary('With required equipment', response['Summary']['PersonsWithRequiredEquipment'])
display_summary('Without required equipment', response['Summary']['PersonsWithoutRequiredEquipment'])
display_summary('Indeterminate', response['Summary']['PersonsIndeterminate'])
print()
return len(response['Persons'])
# Display summary information for supplied summary.
def display_summary(summary_type, summary):
print(summary_type + '\n\tIDs: ', end='')
if (len(summary) == 0):
print('None')
else:
for num, id in enumerate(summary, start=0):
if num == len(summary) - 1:
print(id)
else:
print(str(id) + ', ', end='')
def main():
photo = 'photo-name'
bucket = 'amzn-s3-demo-bucket'
person_count = detect_ppe(photo, bucket)
print("Persons detected: " + str(person_count))
if __name__ == "__main__":
main()
```
------